A rapid motion retrieval technique using simple and discrete representation of motion data

Abstract

In this paper, we propose a rapid motion retrieval technique using dynamic time warping. The frames of the motions are represented by feature vectors whose elements are integer values. The dimensionality of the feature vectors is reduced by using principal component analysis and the values of vector elements are quantized to two bits. A similarity matrix giving distances between the frames is generated for use by dynamic time warping. Preliminary experiments were conducted to find optimum parameter values by evaluating motion retrieval performance. One important feature of the proposed method is that, if the bit length for the frame representation is fixed, the distance between any two frames in any two motions can be found as an element of the similarity matrix without changing its size, which can achieve rapid motion retrieval via dynamic time warping. Experimental comparison with existing methods demonstrated that our proposed technique can complete retrieval tasks over six times faster than a traditional dynamic time warping method, while achieving almost the same levels of accuracy and computation cost as those for the k-d tree method described in [1]. By using simple and discrete representations of frames, the possibilities of achieving rapid retrieval retaining high retrieval accuracy are explored.